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Machine Learning

What are training, validation and test data?

A model needs evaluation on data it did not learn from.

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02 · See it in action

Follow the steps

  1. Define what an independent example means for your task.
  2. Separate the test set before experimenting.
  3. Use validation data or cross-validation to choose settings.
  4. Evaluate the final design once on the held-out test set and report limitations.

Worked example

For 1,000 independent toy examples:
600 training + 200 validation + 200 test
For repeated users: keep each user in only one split.
For forecasting: use chronological splits.

Read the example once, then explain each part aloud in your own words. If it includes Python, you can understand the idea first and run the code later in a local Python environment. Code is shown as text; this page does not execute it.

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